Sentence examples for mass action dynamics from inspiring English sources

Our contributions aid the distinguishability analysis of chemical reaction network (CRN) models with mass action dynamics.

Nevertheless, there is good reason to believe that real systems often deviate from simple mass action dynamics, and this toy model is a special case of those investigated in Liu et al. (1987).

We consider biochemical reaction networks with mass action kinetics where the dynamics are modeled by systems of ordinary differential equations (ODEs).

Regarding the values of the other parameters, our goal here was to compare with the dynamics predicted by mass action kinetics.

From equation (1), it follows that the dynamics of enzymatic chemical reaction networks can be compactly written as (8) x ˙ = - ZL (x ) Exp Z T Ln (x ) + Zv b (x ) A similar expression of the dynamics corresponding to mass action kinetics, in less explicit form, was obtained in [ 31].

To this end, a system-theoretic approach by using Hill-type terms, Michaelis-Menten type and mass action kinetics is introduced in this work and the dynamics is implemented deterministically.

Since they do not include spatial characteristics, mass action kinetics cannot account for this kind of global change of dynamics.

The dynamics governing the promoter kinetics are derived using mass action kinetics with fast reactions that have rate constants in the order of seconds, assumed to be in equilibrium [ 25].

We conclude that for the uniform and clustered gene configurations (even with strong demixing), the individual-based stochastic simulations in 2D show temporal dynamics that are very similar to those predicted by mass action kinetics, even though their salient features are blurred by a high degree of stochasticity.

Evaluation was conducted by setting the glycolytic pathways of E. coli to mass action kinetics and adjusting rate constants to result in same flux and concentration dynamics as the original ARL model [ 21].

The presented methodology is able to predict with accuracy and efficiency the connectivity structure of a chemical reaction network with mass action kinetics and of a gene regulatory network from simulation data even if the dynamics of these systems are non-polynomial (rational) and uncertainties in the data are taken into account.